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Title: Gravitational lensing and the power spectrum of dark matter substructure: Insights from the ETHOS N-body simulations

Journal Article · · Physical Review. D.
 [1];  [2];  [3];  [4];  [5]
  1. Harvard Univ., Cambridge, MA (United States); DOE/OSTI
  2. Harvard Univ., Cambridge, MA (United States)
  3. Harvard Univ., Cambridge, MA (United States); Univ. of New Mexico, Albuquerque, NM (United States)
  4. Univ. of Iceland, Reykjavik (Iceland)
  5. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

Strong gravitational lensing has been identified as a promising astrophysical probe to study the particle nature of dark matter. In this paper we present a detailed study of the power spectrum of the projected mass density (convergence) field of substructure in a Milky Way-sized halo. This power spectrum has been suggested as a key observable that can be extracted from strongly-lensed images and yield important clues about the matter distribution within the lens galaxy. We use two different N-body simulations from the ETHOS framework: one with cold dark matter and another with self-interacting dark matter and a cutoff in the initial power spectrum. Despite earlier works that identified k ≳ 100 kpc–1 as the most promising scales to learn about the particle nature of dark matter we find that even at lower wave numbers—which are actually within reach of observations in the near future—we can gain important information about dark matter. Comparing the amplitude and slope of the power spectrum on scales 0.1 ≲ k/kpc–1 ≲ 10 from lenses at different redshifts can help us distinguish between cold dark matter and other exotic dark matter scenarios that alter the abundance and central densities of subhalos. Furthermore, by considering the contribution of different mass bins to the power spectrum we find that subhalos in the mass range 107 – 108 M are on average the largest contributors to the power spectrum signal on scales 2 ≲ k/kpc–1 ≲ 15, despite the numerous subhalos with masses >108 M in a typical lens galaxy. Lastly, by comparing the power spectra obtained from the subhalo catalogs to those from the particle data in the simulation snapshots we find that the seemingly-too-simple halo model is in fact a fairly good approximation to the much more complex array of substructure in the lens.

Research Organization:
Harvard Univ., Cambridge, MA (United States)
Sponsoring Organization:
USDOE; USDOE Office of Science (SC)
Grant/Contract Number:
SC0019018
OSTI ID:
1613060
Journal Information:
Physical Review. D., Journal Name: Physical Review. D. Journal Issue: 10 Vol. 98; ISSN 2470-0010
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English

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Cited By (14)

ETHOS – an Effective Theory of Structure Formation: detecting dark matter interactions through the Lyman-α forest journal May 2019
Warm dark matter chills out: constraints on the halo mass function and the free-streaming length of dark matter with eight quadruple-image strong gravitational lenses journal December 2019
Addressing astrophysical and cosmological problems with secretly asymmetric dark matter journal July 2019
Beyond subhalos: Probing the collective effect of the Universe’s small-scale structure with gravitational lensing journal July 2019
Direct detection of dark matter substructure in strong lens images with convolutional neural networks journal January 2020
Dark matter microphysics and 21 cm observations journal January 2019
Weak gravitational deflection by two-power-law densities using the Gauss-Bonnet theorem journal June 2019
The Effect of Dark Matter–Dark Radiation Interactions on Halo Abundance: A Press–Schechter Approach journal March 2019
Sloshing of Galaxy Cluster Core Plasma in the Presence of Self-interacting Dark Matter journal September 2019
Mining for Dark Matter Substructure: Inferring Subhalo Population Properties from Strong Lenses with Machine Learning journal November 2019
The effect of dark matter-dark radiation interactions on halo abundance -- a Press-Schechter approach text January 2018
Dark Matter microphysics and 21 cm observations text January 2018
Weak gravitational lensing by two-power-law densities using the Gauss-Bonnet theorem text January 2019
Direct Detection of Dark Matter Substructure in Strong Lens Images with Convolutional Neural Networks text January 2019